Predictability of Anomalous Storm Tracks from Seasonal to Decadal Scales

Gil Compo
CDC

Abstract

This paper is concerned with estimating the predictable variation of
extratropical daily weather statistics ("stormtracks") associated with
sea surface temperature (SST) changes on interannual to interdecadal
scales, and its magnitude relative to the unpredictable noise. The
SST-forced stormtrack signal in each winter in 1950-99 is defined as the
mean stormtrack anomaly obtained in an ensemble of atmospheric general
circulation model (GCM) integrations with prescribed observed SSTs. Two
sets of relatively small (9- to 13-member) ensembles available from two
modeling centers (NCAR and NCEP), with anomalous SSTs prescribed either
globally or in the tropics alone, are used. Since the stormtrack signals
cannot be derived directly from the archived GCM output, they are
diagnosed from the SST-forced winter-mean 200 mb height signals using an
empirical linear stormtrack model (STM). For two particular winters (the
El Nino of JFM 1987 and the La Nina of JFM 1989), the stormtrack signals
and noise are estimated directly, and more accurately, from additional
large (60-member) ensemble runs of the NCEP GCM. The linear STM is shown
to be remarkably successful at capturing the GCM's stormtrack signal in
these two winters, and is thus suitable for estimating the signal in
other winters.

The principal conclusions from this analysis are as follows. A
predictable SST-forced stormtrack signal exists in many winters, but its
strength and pattern can change substantially from winter to winter. The
correlation of the SST-forced and observed stormtrack anomalies is high
enough in the Pacific-North American (PNA) sector to be of practical
use. Most of the SST-forced signal is associated with tropical Pacific
SST forcing; the central Pacific (Nino-4) is somewhat more important
than the eastern Pacific (Nino-3) in this regard. Variations of the
pattern correlation of the SST-forced and observed stormtrack anomaly
fields from winter to winter, and among 5- winter averages, are
generally consistent with variations of the signal strength, and to that
extent are identifiable a priori. Larger pattern correlations for the
5-winter averages in the second half of the 50-yr record, and also the
50-yr stormtrack trend, are consistent with the stronger ENSO SST
forcing in the second half. None of these conclusions, however, apply in
the Euro-Atlantic sector, where the correlations of the SST-forced and
observed stormtrack anomalies are found to be much smaller. Given also
that they are inconsistent with the estimated signal to noise ratios,
substantial GCM error in representing the response in this region to
tropical SST forcing, rather than intrinsically low Euro-Atlantic
stormtrack predictability, is argued to be behind these lower correlations.